Difference between revisions of "LightGBM"
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* [[AI Solver]] | * [[AI Solver]] | ||
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+ | * [[Case Studies]] | ||
+ | ** [[Space/Planets]] | ||
* [[Capabilities]] | * [[Capabilities]] | ||
* [[Gradient Boosting Machine (GBM)]] | * [[Gradient Boosting Machine (GBM)]] |
Revision as of 12:56, 17 August 2020
YouTube search... ...Google search
- AI Solver
- Case Studies
- Capabilities
- Gradient Boosting Machine (GBM)
- XGBoost; eXtreme Gradient Boosted trees
- Multiclassifiers; Ensembles and Hybrids; Bagging, Boosting, and Stacking
- (Boosted) Decision Tree
- Boosted Random Forest
- Boosting | Wikipedia
- Boosted Decision Tree Regression | Microsoft
- LightGBM, Light Gradient Boosting Machine - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. LightGBM is under the umbrella of the DMTK project of Microsoft | GitHub
Microsoft's gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed and efficient by using histogram-based algorithms, which bucket continuous feature (attribute) values into discrete bins. This speeds up training and reduces memory usage.